Dr. Matthew B. Blaschko
Visual Geometry Group
University of Oxford
Information Engineering Building
Parks Road, Oxford OX1 3PJ
United Kingdom

Visitor Directions

Voice: +44 1865 283057
Fax: +44 1865 283145
Mobile: +44 7794 871443
Email:

IJCV Special Issue on Structured Prediction and Inference Guest Editors: Matthew B. Blaschko and  Christoph H. Lampert

I have moved to the École Centrale Paris. Please see my new webpage.

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I am interested in the interface between machine learning and computer vision. Areas I have worked on include multiple instance learning, object detection and localization, multiple kernel learning, structured output regression, clustering, and taxonomy discovery.

News:

• I will be joining the applied mathematics faculty of the École Centrale Paris in October, 2011.
• I am on the senior program committee for AISTATS 2012.
• I gave a tutorial on Structured Prediction and Inference in Computer Vision at BMVC 2011 in Dundee, Scotland.
• I gave a tutorial at the Twentieth Annual Computational Neuroscience Meeting CNS*2011 in Stockholm, Sweden.
• I received a best reviewer award for CVPR 2011.
• I organized the Oxford Robotics Research Group Seminars from January to September, 2011.
• I have been awarded a Newton International Fellowship.
• I am guest editor of the International Journal of Computer Vision special issue on Structured Prediction and Inference.
• Christoph Lampert and I gave short course on Kernel Methods in Computer Vision at CVPR 2009. Slides are available here: Part 1 Part 2
• We held a reading group on structured output learning in the Visual Geometry Group, Spring-Summer 2009.
• Some additional information is available from my old homepage at the Max Planck Institute for Biological Cybernetics.

Students Advised:

• Ben Mather, University of Oxford, MEng 2011.
• Shah Ruhul Amin, University of Oxford, MEng 2010.
• Jacquelyn A. Shelton, Universität Tübingen, M.Sc. 2010.
  Thesis: Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data

Publications:

• Rahtu, E., J. Kannala, and M. B. Blaschko: Learning a Category Independent Object Detection Cascade. International Conference on Computer Vision (ICCV), 2011.
   
• Vedaldi, A., M. B. Blaschko, and A. Zisserman: Learning Equivariant Structured Output SVM Regressors. International Conference on Computer Vision (ICCV), 2011.
   
• Blaschko, M. B.: Branch and Bound Strategies for Non-maximal Suppression in Object Detection. International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (EMMCVPR), 2011. [doi]
   
• Blaschko, M. B., J. A. Shelton, A. Bartels, C. H. Lampert and A. Gretton: Semi-supervised Kernel Canonical Correlation Analysis with Application to Human fMRI. Pattern Recognition Letters, 32(11):1572-1583, 2011. [doi]
   
• Blaschko, M. B., A. Vedaldi and A. Zisserman: Simultaneous Object Detection and Ranking with Weak Supervision. Proceedings of the Twenty-Fourth Annual Conference on Neural Information Processing Systems (NIPS 2010)
   
• Shelton, J. A., M. B. Blaschko, A. Gretton, J. Müller, E. Fischer and A. Bartels, Similarities in Resting State and Feature-driven Activity: Non-parametric Evaluation of Human fMRI. NIPS'10 Workshop on Learning and Planning from Batch Time Series Data, 2010.
   
• Shelton, J. A., M. B. Blaschko, and A. Bartels: Augmentation of fMRI Data Analysis using Resting State Activity and Semi-supervised Canonical Correlation Analysis. Women in Machine Learning Workshop (WiML 2010), Vancouver, BC, Canada 2010.
   
• Tuytelaars, T., C. H. Lampert, M. B. Blaschko and W. Buntine: Unsupervised Object Discovery: A Comparison. International Journal of Computer Vision (IJCV), 88(2):284-302, 2010. [code; doi]
   
• Blaschko, M. B., J. A. Shelton and A. Bartels: Augmenting Feature-driven fMRI Analyses: Semi-supervised Learning and Resting State Activity. Proceedings of the Twenty-Third Annual Conference on Neural Information Processing Systems (NIPS 2009)
   
• Blaschko, M. B. and C. H. Lampert: Object Localization with Global and Local Context Kernels. British Machine Vision Conference (BMVC), 2009. [video]
   
• Lampert, C. H., M. B. Blaschko and T. Hofmann: Efficient Subwindow Search: A Branch and Bound Framework for Object Localization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(12):2129-2142, 2009. [code; doi]
   
• Shelton, J. A., M. B. Blaschko, C. H. Lampert and A. Bartels: Semi-supervised Analysis of Human fMRI. Berlin Brain-Computer Interface Workshop (BBCI), 2009.
   
• Shelton, J., M. B. Blaschko and A. Bartels: Semi-supervised Subspace Analysis of Human Functional Magnetic Resonance Imaging Data. Max Planck Institute for Biological Cybernetics Tech Report (185) (05 2009)
   
• Lampert, C. H. and M. B. Blaschko: Structured Prediction by Joint Kernel Support Estimation. Machine Learning, 77(2-3):249-269, 2009. [doi]
   
• Blaschko, M. B.: Kernel Methods in Computer Vision: Object Localization, Clustering, and Taxonomy Discovery. Doctoral Thesis, Max Planck Institute for Biological Cybernetics, Awarded by the Technische Universität Berlin, 2009.
   
• Blaschko, M. B. and A. Gretton: Learning Taxonomies by Dependence Maximization. Proceedings of the Twenty-Second Annual Conference on Neural Information Processing Systems (NIPS 2008), 1-8. (Eds.) Koller, D., D. Schuurmans, Y. Bengio, L. Bottou (01 2009)
   
• Lampert, C. H. and M. Blaschko: Joint Kernel Support Estimation for Structured Prediction. NIPS 2008 Workshop on "Structured Input - Structured Output" 2008, 76 (12 2008)
   
• Blaschko, M. B. and A. Gretton: Taxonomy Inference Using Kernel Dependence Measures. Max Planck Institute for Biological Cybernetics Tech Report (181) (11 2008)
   
• Blaschko, M. B. and C. H. Lampert: Learning to Localize Objects with Structured Output Regression. Computer Vision: ECCV 2008, 2-15. (Eds.) Forsyth, D. A., P. H.S. Torr, A. Zisserman, Springer, Berlin, Germany (10 2008) [Note: Best Student Paper Award; code; doi]
   
• Blaschko, M. B., C. H. Lampert and A. Gretton: Semi-Supervised Laplacian Regularization of Kernel Canonical Correlation Analysis. Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2008, 133-145. (Eds.) Daelemans, W., B. Goethals, K. Morik, Springer, Berlin, Germany (08 2008) [doi]
   
• Blaschko, M. B. and A. Gretton: A Hilbert-Schmidt Dependence Maximization Approach to Unsupervised Structure Discovery. Proceedings of the 6th International Workshop on Mining and Learning with Graphs (MLG 2008), 1-3 (07 2008)
   
• Blaschko, M. B. and C. H. Lampert: Correlational Spectral Clustering. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 1-8, IEEE Computer Society, Los Alamitos, CA, USA (06 2008) [code; doi]
   
• Lampert, C. H., M. B. Blaschko and T. Hofmann: Beyond Sliding Windows: Object Localization by Efficient Subwindow Search. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2008), 1-8, IEEE Computer Society, Los Alamitos, CA, USA (06 2008) [Note: Best paper award; code; doi]
   
• Lampert, C. and M. B. Blaschko: A Multiple Kernel Learning Approach to Joint Multi-Class Object Detection. Pattern Recognition: Proceedings of the 30th DAGM Symposium, 31-40. (Eds.) Rigoll, G. Springer, Berlin, Germany (06 2008) [Note: Main Award DAGM 2008; doi]
   
• Blaschko, M. B., T. Hofmann and C. H. Lampert: Efficient Subwindow Search for Object Localization. Max Planck Institute for Biological Cybernetics Tech Report (164) (08 2007)
   
• Blaschko, M. B. and T. Hofmann: Conformal Multi-Instance Kernels. NIPS 2006 Workshop on Learning to Compare Examples, 1-6 (12 2006)
   
• Lisin, D. A., M. A. Mattar, M. B. Blaschko, M. C. Benfield and E. G. Learned-Miller: Combining Local and Global Image Features for Object Class Recognition. Proceedings of IEEE Workshop on Learning in Computer Vision and Pattern Recognition (in conjunction with CVPR), 47 (06 2005) [doi]
   
• Blaschko, M. B.: Support Vector Classification of Images with Local Features. M.S. Thesis, University of Massachusetts Amherst, Dept. of Computer Science (05 2005)
   
• Blaschko, M. B., G. Holness, M. A. Mattar, D. Lisin, P. E. Utgoff, A. R. Hanson, H. Schultz, E. M. Riseman, M. E. Sieracki, W. M. Balch and B. Tupper: Automatic In Situ Identification of Plankton. Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05), 79 - 86 (01 2005) [doi]
   
• Shapiro, M. D. and M. B. Blaschko: Stability of Hausdorff-based Distance Measures. Visualization, Imaging, and Image Processing, 1-6 (09 2004)
   
• Shapiro, M. D. and M. B. Blaschko: On Hausdorff Distance Measures. University of Massachusetts Amherst, Computer Science Dept. Technical report (08 2004)